2027 Spring Co op Biologics Design and AI

About The Job

Join Sanofi for a 6-month Spring Co-op in Biologics Design and AI in Cambridge, MA. This role focuses on bridging Large Language Models (LLMs) and autonomous AI agents with biophysical protein predictive models. You will work with computational biologists and AI scientists to build intelligent, agentic workflows that reason over structural data, orchestrate predictive tools, and map protein sequences to critical therapeutic properties, accelerating the biologics pipeline.

Main Responsibilities

• LLM Fine-Tuning & Cross-Modal Adaptation:
• Fine-tune conversational, natural language LLMs to interface with and reason over data from specialized protein prediction models.
• Adapt LLMs using parameter-efficient techniques (e.g., LoRA, PEFT) to understand protein sequences, structural embeddings, and biophysical constraints.
• Build hybrid architectures to enhance the accuracy of critical antibody and nanobody property predictions (e.g., binding affinity, thermal stability).
• Collaboration & Reporting:
• Partner with experimental protein engineers and computational biologists to understand biological constraints and define agent objectives.
• Validate model predictions.
• Present methodologies, insights, and model performance to cross-functional R&D teams.

Requirements & Tech Stack

• Currently pursuing a Master’s or PhD degree in Computer Science, Data Science, Computational Biology, Bioinformatics, Bioengineering, or related field, with plans to graduate by Spring 2027 (or 2028).
• Must be permanently authorized to work in the U.S. and not require visa sponsorship.
• Must be enrolled in an accredited college or university throughout the duration of the co-op.
• Must be able to relocate to Cambridge, MA, and work 40 hours/week, Monday to Friday for the full duration.
• Strong programming skills in Python and standard data science libraries.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, or JAX.
• Experience using state-of-the-art AI tools for biology (e.g., Protein LLMs, AlphaFold, Rosetta).
• Excellent problem-solving and communication skills.
• Fluent in English.

Preferred Qualifications

• Previous academic projects or industry experience demonstrating the application of NLP, LLMs, or agentic workflows to complex scientific problems.
• Familiarity with biological data, specifically protein sequences and 3D structures.
• Basic domain knowledge in immunology, structural biology, or biophysics.
• Hands-on experience with LLM fine-tuning methodologies and orchestration frameworks.

Compensation

• Hourly rate: $47 - $60